In 3GPP standards, heterogeneous network deployments have been defined as deployments where low-power nodes of different transmit powers are placed throughout a macro-cell layout. Examples of low-power nodes include micro, pico, and femto nodes. Heterogeneous network deployments provide capacity extension in certain areas such as traffic hotspots. A traffic hotspot is a small geographical area with a higher user density and/or higher traffic intensity than the surrounding area. Placing a low-power node such as a pico node at a traffic hotspot can adapt a network according to traffic needs and environment, thus enhancing the network's performance. However, interference characteristics in a heterogeneous deployment are significantly different than in a homogeneous deployment, in both downlink and uplink. Also in a heterogeneous network deployment, traffic distribution is often non-uniform and uplink transmissions generally experience high interference due to the co-existence of both small and large cells. It is often challenging to ensure efficient network operation and superior user experience in a heterogeneous network deployment. One common problem related to heterogeneous networks is that it is often difficult for a wireless device to perform measurements on signals transmitted from a low-power node in a heterogeneous network due to interference from neighboring high-power nodes. Yet accurate signal estimates and measurements are needed for important functionalities such as cell search, cell identification, handover, Radio Link Management (RLM) and Radio Resource Management (RRM), etc.
It is generally known that a received pilot power estimate for a neighbor cell may be obtained by applying a scaling factor to the estimated received synchronization channel power of this neighbor cell. The scaling factor may be calculated as a ratio of the estimated received pilot power in the serving cell over the estimated received synchronization channel power of the serving cell. In this approach, the scaling factor is calculated as a ratio of signals of two different types, which may have no correlation with each other. Further such approach is not applicable in a cell that does not transmit pilot signals, for example, in a network where new carrier types are used and no cell-specific reference signals (CRS) are transmitted.
There is a need for improved methods and apparatus that can be used to obtain reliable and accurate signal estimates for a cell, both serving and neighboring, that may be served by a low-power node in a high interfering environment.